Submission declined on 19 June 2025 by CF-501 Falcon (talk). This draft is not adequately supported by reliable sources. Wikipedia's verifiability policy requires that all content be supported by reliable sources. Reliable sources include: reputable newspapers, magazines, academic journals, and books from respected publishers. Unacceptable sources include: personal blogs, social media, predatory publishers, most tabloids, and websites where anyone can contribute. Replace any unreliable sources with high-quality sources. If you cannot find a reliable source for the material, it should be removed. This draft's references do not show that the subject meets Wikipedia's criteria for inclusion for organizations and companies. The draft requires multiple published secondary sources that: provide significant coverage: discuss the subject in detail, excluding routine coverage like product launches, staff appointments, or financial reports and listings in databases or listicles; are reliable: from reputable outlets with editorial oversight; are independent: not connected to the subject, such as press releases, the subject's own website, or sponsored content. Please add references that meet all three of these criteria. If none exist, the subject is not yet suitable for Wikipedia. If you would like to continue working on the submission, click on the "Edit" tab at the top of the window. If you have not resolved the issues listed above, your draft will be declined again and potentially deleted. If you need extra help, please ask us a question at the AfC Help Desk or get live help from experienced editors. Please do not remove reviewer comments or this notice until the submission is accepted. Where to get help If you need help editing or submitting your draft, please ask us a question at the AfC Help Desk or get live help from experienced editors. These venues are only for help with editing and the submission process, not to get reviews. If you need feedback on your draft, or if the review is taking a lot of time, you can try asking for help on the talk page of a relevant WikiProject. Some WikiProjects are more active than others so a speedy reply is not guaranteed. How to improve a draft Wikipedia:Contributing to Wikipedia – a basic overview on how to edit Wikipedia. Help:Wikitext – how to use the markup Help:Referencing for beginners – how to include references Wikipedia:Article development – how to develop your article Wikipedia:Writing better articles – how to improve your article Wikipedia:Verifiability – make sure your article includes reliable third-party sources You can also browse Wikipedia:Featured articles and Wikipedia:Good articles to find examples of Wikipedia's best writing on topics similar to your proposed article. Improving your odds of a speedy review To improve your odds of a faster review, tag your draft with relevant WikiProject tags using the button below. This will let reviewers know a new draft has been submitted in their area of interest. For instance, if you wrote about a female astronomer, you would want to add the Biography, Astronomy, and Women scientists tags. Add tags to your draft Editor resources Easy tools: Citation bot (help) | Advanced: Fix bare URLs Declined by CF-501 Falcon 11 months ago. Last edited by Zh.Sarkisova 3 months ago. Reviewer: Inform author. Resubmit Please note that if the issues are not fixed, the draft will be declined again.

Submission declined on 17 June 2025 by Pythoncoder (talk). This draft reads like an advertisement. Wikipedia is an encyclopedia, not a platform for promotion or marketing. Drafts that are exclusively promotional may be deleted without notice. Wikipedia articles must be written neutrally in a formal, impersonal, and dispassionate way. They should not read like a blog post, advertisement, or fan page. Rewrite the draft to remove: promotional language: see Words to watch; personal commentary: opinions or direct addresses to the reader; informal language. Instead, only summarize in your own words a range of independent, reliable, published sources that discuss the subject. If you have a conflict of interest (e.g. you are the subject, an employee, or a relative) or are being paid to edit, you must disclose this to comply with Wikipedia's Terms of Use. Declined by Pythoncoder 11 months ago.

Submission declined on 17 June 2025 by Pythoncoder (talk). This draft reads like an advertisement. Wikipedia is an encyclopedia, not a platform for promotion or marketing. Drafts that are exclusively promotional may be deleted without notice. Wikipedia articles must be written neutrally in a formal, impersonal, and dispassionate way. They should not read like a blog post, advertisement, or fan page. Rewrite the draft to remove: promotional language: see Words to watch; personal commentary: opinions or direct addresses to the reader; informal language. Instead, only summarize in your own words a range of independent, reliable, published sources that discuss the subject. If you have a conflict of interest (e.g. you are the subject, an employee, or a relative) or are being paid to edit, you must disclose this to comply with Wikipedia's Terms of Use. Declined by Pythoncoder 11 months ago.

Submission declined on 17 June 2025 by DoubleGrazing (talk). This draft reads like an advertisement. Wikipedia is an encyclopedia, not a platform for promotion or marketing. Drafts that are exclusively promotional may be deleted without notice. Wikipedia articles must be written neutrally in a formal, impersonal, and dispassionate way. They should not read like a blog post, advertisement, or fan page. Rewrite the draft to remove: promotional language: see Words to watch; personal commentary: opinions or direct addresses to the reader; informal language. Instead, only summarize in your own words a range of independent, reliable, published sources that discuss the subject. If you have a conflict of interest (e.g. you are the subject, an employee, or a relative) or are being paid to edit, you must disclose this to comply with Wikipedia's Terms of Use. This draft's references do not show that the subject meets Wikipedia's criteria for inclusion for organizations and companies. The draft requires multiple published secondary sources that: provide significant coverage: discuss the subject in detail, excluding routine coverage like product launches, staff appointments, or financial reports and listings in databases or listicles; are reliable: from reputable outlets with editorial oversight; are independent: not connected to the subject, such as press releases, the subject's own website, or sponsored content. Please add references that meet all three of these criteria. If none exist, the subject is not yet suitable for Wikipedia. Declined by DoubleGrazing 11 months ago.

• Comment: Only Awards and Recognition has references; you will need to find sources for the entire draft. CF-501 (talk · contribs) 00:16, 19 June 2025 (UTC)

• Comment: Resubmitted without meaningful improvement. —pythoncoder (talk | contribs) 18:32, 17 June 2025 (UTC)

DataRoot Labs is a technology company that develops and implements artificial intelligence (AI), machine learning (ML), and data engineering systems for clients across multiple industries. Founded in 2016^[1], the company specializes in AI consulting and custom AI/ML development, with expertise in generative AI, natural language processing (NLP), computer vision, reinforcement learning, and edge ML.

Headquartered in Kyiv, Ukraine, DataRoot Labs serves a global client base and is known for leveraging Ukrainian engineering talent. It also operates an educational initiative focused on AI and data science training.

DataRoot Labs was founded in 2016^[2] by Max Frolov, Ivan Didur, Vasyl Koida, and Yuliya Sychikova. Since its inception, the company has focused exclusively on AI development and research.

In 2017, it launched DataRoot University (DRU), a free online education platform offering machine learning and data engineering courses. As of 2025, more than 6,000 students have participated.^[3] Max Frolov, co‑founder and CEO, was named to Kyiv Post’s “Top 30 Under 30” in 2019 for launching the free‑to‑access DRU.^[4]

In 2025 DataRoot Labs in partnership with UFTM, opened an AI Space in Kyiv Polytechnic Instute.

DataRoot Labs is an artificial intelligence (AI) consulting and development company. Its services include natural language processing (NLP), computer vision, machine learning (ML), data engineering, MLOps, AI product development, and AI-powered hardware solutions.^[5] The company provides end-to-end support for AI system design, development, training, deployment, and optimization.

Its NLP capabilities include the development of custom pipelines, multimodal large language model (LLM) training and fine-tuning, knowledge-based LLMs, and autonomous LLM agents. In computer vision, the company develops object detection, tracking, segmentation, and simulation systems. Its data engineering services focus on pipeline development, cloud data platforms, data warehousing, and lakehouse architecture. It also works on AI-enabled robotics, smart IoT devices, and sensor-based applications.^[6]

DataRoot Labs delivers solutions across multiple industries, including automotive, logistics, transportation, manufacturing, healthcare, cybersecurity, e-commerce, retail, real estate, media, fintech, and sports.^[7] Independent client reviews describe the firm as “professional and responsive,” noting projects in natural language processing, computer vision, and AI product development.^[8][9]

The company is a member of the NVIDIA Inception Program, a global accelerator supporting startups that are advancing innovation in AI and data science.

DataRoot Labs has received recognition for its work in artificial intelligence and software development. In 2022, the company was included in Forbes’ list of the top 10 AI consulting firms^[10] and was highlighted in VentureBeat^[11] for its contributions to AI research and development. It was also named a 5‑Star Software and Technology Provider by HRReporter.^[12] Additionally, the company won the Technology Innovator Award for Best AI Development Company^[13] and was a winner of a Kaggle competition hosted by CareerVillage for developing a machine learning-powered recommendation engine.^[14]

• Official website
• DataRoot University
• Yuliya Sychikova